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Thursday 8 October

Chemical Physics

Predictive Synthesis of MOFs and COFs

Bin Feng, Reid A. Coyle, Shyam Chand Pal et al. (+3 more)

Predictive synthesis concerns the prospective modeling of how a targeted structure can be realized. The synthesis of metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) intrinsically involves a multidimensional space of interdependent variables, posing a challenge for bench chemists to parameterize and predict. In this Perspective, we discuss the evolution from chemical-intuition-driven experimentation toward the integration of artificial intelligence (AI) and machine learning (ML) in the laboratory. By virtue of prior knowledge, uncertainty, and experimental failure in determining what should be attempted next, we envision predictive synthesis progressing from static recipe recommendation toward real-time control and transferable principles of framework formation. In this context, the significance lies in transforming trial-and-error practice into a means of measurable chemical reasoning, thereby accelerating crystalline materials discovery and advancing synthetic chemistry.
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All authors Bin Feng, Reid A. Coyle, Shyam Chand Pal, Peter Walther, Saeun Park, Zhiling Zheng

Chemical Physics · Cross-listed from physics.optics

Theory of Disorder-Induced Multimode Coupling in a Fabry-Pérot Cavity

Wei-Kuo Li and Hsing-Ta Chen

Strong light–matter interactions have attracted significant interest in physical chemistry due to the potential for modifying molecular processes by hybridizing with cavity photons and forming polaritonic states. However, for a disordered molecular ensemble within an optical cavity capable of supporting multiple photon modes, theoretical understanding of multimode polaritons remains incomplete, particularly regarding whether and how distinct photon modes are mutually coupled through molecules. In this work, we generalize the collective mode expansion formalism to incorporate multiple photonic modes and show that spatial and orientational disorder in the light–matter coupling strength (originating from dipole orientation fluctuations and photonic field inhomogeneity) can mediate cross-mode coupling. This disorder-induced coupling allows for energy transfer to otherwise unexcited photon modes through a mechanism termed disorder-induced multimode activation (DIMA). Using an effective one-dimensional Fabry–Pérot cavity as a test system, we demonstrate that the cross-mode energy transfer through DIMA can be controlled by changing the molecular layer thickness and the optical properties of the mirrors. Furthermore, we show that DIMA is robust against weak energetic disorder. This mechanistic understanding lays the foundation for a systematic control of multimode photon coupling using disorder-induced effects.
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Chemical Physics · Cross-listed from math.NA

Fourier Transform-Based Computation of Two-Electron Four-Center Coulomb Repulsion Integrals

William Chen, Lior Silberman, Ury Segal et al. (+1 more)

We present a Fourier-based method for evaluating two-electron four-center Coulomb repulsion integrals over Slater-type orbitals. Spherical Fourier-Bessel coefficients of the convolution factors are precomputed and reused. Since the spherical part of the integral can be evaluated directly, there remains only a one-dimensional quadrature problem in the radial direction. For the ten reference integrals reported here, the largest absolute discrepancy is $1.7\times10^{-9}$. A preliminary resident-cache benchmark computes approximately $4.2\times10^5$ unique integrals per second on an NVIDIA V100 at the contraction stage.
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All authors William Chen, Lior Silberman, Ury Segal, Chen Greif

Chemical Physics

The Reference Set Is Not the Answer Set: GEOM-DRUGS Is Missing Low-Energy Conformers on Its Own Energy Surface

Alvand Vahediahmar, Aaron Zweig, Mingxuan Zhang et al. (+1 more)

Machine-learned conformer generators are scored on GEOM-DRUGS by proximity to a reference ensemble that standard benchmark metrics implicitly treat as ground truth. We test whether that finite set is complete on the GFN2-xTB surface used to construct it. Across five public generators, settled, low-energy structures remain outside the $0.75$\,Å reference radius after removing reflections, incorrect stereochemistry, and post-relaxation connectivity changes ($2.3$–$7.0\%$ of submitted conformers, depending on architecture). In a targeted DFT audit, $107$ of $113$ chemically screened novel/reference pairs remain outside that radius after full $\omega$B97X-D3BJ re-optimization. A threshold-free complementary test needs no radius and no energy window at all: on $15.0\%$ $[8.0, 22.0]$ of molecules some generator has already found a chemically intact structure lying below the entire released ensemble. A complementary CREST search reproduces the minimum released in $65$ of $69$ molecules, and in $11$ of them it reaches more than $0.5$\,kcal/mol below the complete released ensemble. Augmenting the references with conformers proposed by held-out architectures raises absolute coverage-precision for every generator tested, by $1.48$–$2.99$ points. Together, these results show that GEOM-DRUGS precision is sensitive not only to generator quality but also to incomplete reference support.
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All authors Alvand Vahediahmar, Aaron Zweig, Mingxuan Zhang, Elham Azizi

Chemical Physics

MolP2SBench: Do LLMs Really Reason from Molecular Properties to Structure?

Yuhang Xie, Zhiyi Shi, Zeyi Zhang et al. (+4 more)

Large language models (LLMs) are increasingly used in molecular discovery and structure elucidation, where decisions depend on physical observations. Existing evaluations primarily focus on end-to-end molecular reconstruction, where correct predictions do not necessarily indicate reliance on the supplied properties. We introduce MolP2SBench, a benchmark for molecular property-to-structure (P2S) reasoning in LLMs. Each task presents a masked molecular scaffold with given properties and asks the model to select the missing structure from plausible candidates. We shuffle or replace properties to test reliance on correct property-structure pairing and responsiveness to counterfactual property changes. A channel-wise leaderboard uses Property-Grounded Recovery (PGR), giving equal weight to source and counterfactual recovery. Evaluating seven models, we find that LLMs can use physical properties for structure prediction, but performance varies substantially across property types. Higher accuracy with a property does not necessarily imply greater responsiveness to it: a model may benefit more from $^1$H NMR than from $^{13}$C NMR, yet be less likely to change its prediction when the $^1$H data is replaced. LLM performance also need not reflect the relative difficulty of these properties for human chemists. Although UV-Vis spectra provide less direct structural information than NMR spectra, Astra achieves higher accuracy with UV-Vis data than with NMR peaks. MolP2SBench supports studying how LLMs extract and use physical-property information, revealing patterns that may differ from conventional chemical intuition and providing a foundation for more reliably property-grounded models for molecular and quantum-chemical inference. Code and dataset: https://github.com/DUAL-Xiao/MolP2SBench.
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All authors Yuhang Xie, Zhiyi Shi, Zeyi Zhang, Zhisheng Qi, Yushun Dong, Yu Wang, Xiongye Xiao

Chemical Physics

MERCE: Method-Space Correlation Energy Extrapolation toward High-Rank Coupled Cluster Accuracy

Mateusz Witkowski, Szymon Śmiga, Pavlo O. Dral et al. (+1 more)

Energy extrapolation is a well-established strategy for approaching quantum-chemical limits without performing prohibitively expensive calculations. Complete basis set extrapolation is widely used, whereas extrapolation across electronic structure methods remains much less developed. Method-Space Effective-Rank Correlation Energy Extrapolation (MERCE) is introduced as an adaptive effective-rank framework for estimating high-rank finite-basis correlation energies from second-order Moller-Plesset perturbation theory (MP2), coupled cluster with single and double excitations (CCSD), and CCSD with perturbative triples [CCSD(T)]. The method assigns adaptive effective ranks to MP2 and CCSD(T) from the local MP2-CCSD-CCSD(T) correlation energy pattern and fits a compact three-point extrapolation form for each system. A hierarchical model-selection protocol balances cross-dataset transferability, maximum dataset-level mean absolute error (MAE) ratios, robustness on developmental sets referenced to full configuration interaction (FCI), size-consistency defects, and performance for A24 noncovalent interaction energies. Across the chemically diverse benchmarks used during model development, the selected MERCE model substantially reduces CCSD(T) errors and frequently improves upon the tested higher-rank coupled cluster baselines. Transferability is further assessed using calculations performed only after the functional form and parameters were frozen. Formal nonadditivity is quantified using artificial noninteracting pairs and the actual A24 and selected S66 component calculations.
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All authors Mateusz Witkowski, Szymon Śmiga, Pavlo O. Dral, Ireneusz Grabowski

Chemical Physics

MAST: Motif-Augmented Diffusion with Search Tree for Spectroscopic Molecular Structure Elucidation

Chenghao Jia, Mengdi Liu, Hong Chang et al. (+2 more)

Elucidating molecular structures from spectra is a foundational problem in chemical and materials characterization, yet remains challenging due to spectral ambiguity and the vast molecular space. Although recent diffusion-based generators show strong promise for spectra-conditioned elucidation, existing methods struggle to learn robust spectra-structure relationships from limited paired data when relying solely on global spectral representation. Moreover, the repeated full sampling inference strategy incurs substantial computation overhead. To address these limitations, we propose MAST, a Motif-Augmented diffusion framework with Search Tree, for joint 2D-3D spectroscopic molecular structure elucidation. MAST introduces explicit, interpretable motif priors as intermediate evidences throughout denoising, reducing conditional ambiguity and facilitating spectra-conditioned optimization. We further cast diffusion sampling as reward-guided tree search to prioritize high-reward denoising trajectories, yielding a compact set of spectra-consistent candidates under limited budgets. On the QM9S multi-spectra benchmark, MAST achieves 94.89% exact recovery and improves 3D fidelity, while preserving high chemical validity and stability. Code is available at https://github.com/Jia040223/MAST.
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All authors Chenghao Jia, Mengdi Liu, Hong Chang, Shiguang Shan, Xilin Chen

Chemical Physics

Gas-phase chemistry of $\mathrm{C}_3\mathrm{H}_3^+$: a key building block for carbon mass growth in space

Corentin Rossi, Jean-Christophe Loison, Anne P. Rasmussen et al. (+4 more)

The gas-phase chemistry of $\mathrm{C}_3\mathrm{H}_3^+$ plays a central role in the growth of carbonaceous species across a wide range of environments, from combustion systems to interstellar media. However, the presence of multiple isomers, primarily the linear propargyl cation and the cyclic cyclopropenyl cation, has so far prevented the determination of reliable isomer-specific reaction kinetics. In this work, we combine tunable vacuum-ultraviolet (VUV) photoionization with controlled ion–molecule reaction measurements to selectively produce and probe the reactivity of $\mathrm{C}_3\mathrm{H}_3^+$ isomers. By employing a titration approach, we extract isomer-specific reaction rate coefficients and branching ratios for reactions of $\mathrm{C}_3\mathrm{H}_3^+$ with $\mathrm{C}_2\mathrm{H}_4$, $\mathrm{C}_3\mathrm{H}_4$, and $\mathrm{C}_3\mathrm{H}_6$. Our results demonstrate a strong contrast in reactivity: the most stable cyclic isomer is found to be essentially unreactive under the investigated conditions, whereas the linear isomer exhibits efficient and diverse chemistry leading to the formation of larger hydrocarbon ions. In particular, the formation of $\mathrm{C}_6\mathrm{H}_5^+$ is observed, providing an important intermediate in pathways toward aromatic species. These findings help resolve long-standing ambiguities in previously reported rate coefficients and provide new quantitative constraints for kinetic and astrochemical models. More broadly, this work highlights the importance of isomer-specific chemistry in carbon growth processes and demonstrates the effectiveness of VUV-based photoionization methods for disentangling complex reaction networks in the gas phase.
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All authors Corentin Rossi, Jean-Christophe Loison, Anne P. Rasmussen, Roland Thissen, Nandana Pattathadathil, Christian Alcaraz, Ugo Jacovella

Chemical Physics · Cross-listed from cond-mat.stat-mech

Mutual Linearity of Complexes in Chemical Reaction Networks

Pedro E. Harunari, Guilherme Fiusa and Matteo Polettini

Exact statements about how a system far from equilibrium responds to changes in its rate constants are scarce beyond linear response, yet they are central to the control of biochemical networks. A notable exception is mutual linearity: in a jump process, controlling the rates of a single transition makes any two stationary probabilities obey an exact affine relation, arbitrarily far from equilibrium. With nonlinear mass-action kinetics, and conservation laws in place of a normalization, chemical reaction networks seem to defy mutual linearity since species concentrations obey no such relation. We show that it was there all along, in the complexes' activities (mass-action monomials) rather than in the concentrations of species. For zero-deficiency networks with a single linkage class, controlling one reaction makes any three stationary activities obey a linear relation whose coefficients are independent of the controlled rate constants, the conserved quantities (hence the initial state), and even of the stoichiometry of complexes. This predicts hidden activities and bounds the activity ratios the control can reach, while a violation signals nonzero deficiency or multiple linkage classes.
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Chemical Physics

Unitary Coupled Cluster Nuclear Shielding Constants in a Quantum Linear Response Framework

Juliane H. Fuglsbjerg, Sonia Coriani, Jacob Kongsted et al. (+1 more)

We present calculations of nuclear shielding constants, a key ingredient in nuclear magnetic resonance spectroscopy, within a quantum-computing-suitable framework. We employ quantum linear response (qLR) theory in combination with the unitary coupled cluster (UCC) ansatz and its orbital-optimized (oo-UCC), factorized (fUCC), and orbital-optimized factorized (oo-fUCC) variants. The methods are assessed for seven small molecules against CASCI, CASSCF, CCSD, and CCSD(T) reference calculations. The different UCC-based qLR approaches yield shielding constants in good agreement with comparable classical methods. Factorization, which is necessary for quantum-computing implementations, has only a negligible effect on the calculated shielding constants. Orbital optimization, in contrast, leads to substantial improvements, with oo-UCC and oo-fUCC showing markedly better agreement with CCSD and CCSD(T). Our results establish oo-fUCC combined with qLR as a promising approach for computing nuclear shielding constants on quantum computers.
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All authors Juliane H. Fuglsbjerg, Sonia Coriani, Jacob Kongsted, Stephan P. A. Sauer

Chemical Physics

Optical absorption spectra from the $GW$-Bethe-Salpeter framework for thousands of atoms

Maximilian Graml, Ritaj Tyagi, Rémi Pasquier et al. (+2 more)

The frequency-dependent absorption and emission of light determine the colors of matter and underpin today's technologies, from solar cells to light-emitting diodes. Predicting optical properties from first principles remains a computational challenge, especially for large and disordered systems. The $GW$ plus Bethe-Salpeter equation ($GW$-BSE) approach provides predictive accuracy for optical properties, but conventional implementations become costly as system size grows. Here, we present a $GW$-BSE framework combining real-time propagation, atom-centered basis sets, and a locally optimized real-space resolution of the identity. The cost of each propagation step scales quadratically with system size and roughly equals the cost of one self-consistent-field iteration in a density-functional calculation with a semilocal functional. This computational efficiency allows us to calculate the absorption spectrum of a nanographene containing 4616 atoms and opens a path toward routine calculations of optical properties for large disordered systems.
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All authors Maximilian Graml, Ritaj Tyagi, Rémi Pasquier, Štěpán Marek, Jan Wilhelm

Chemical Physics

Predictable Accuracy of Martini 3 Absolute Protein-Ligand Binding Free Energies across 15 Targets

Luis J. Walter and Tristan Bereau

Alchemical free-energy calculations predict protein-ligand binding affinities with close-to-experimental accuracy, but their cost restricts them to small sets of ligands. Coarse-grained (CG) models such as Martini 3 retain a rigorous statistical-mechanical treatment at a fraction of this cost, yet their accuracy for protein-ligand binding has not been assessed systematically. Here, we compute absolute binding free energies for 172 ligands across 15 protein targets with a Martini 3 double-decoupling protocol and compare them against atomistic FEP+ and OpenFE references. Martini underbinds for every target, by 2.7 to 8.7 kcal/mol. This offset is systematic: it comprises a uniform contribution that grows with the number of charged pocket residues. A linear model in this number, which requires only the protein structure, reduces the mean absolute error from 5.7 to 1.2 kcal/mol in leave-one-out cross-validation, close to the 1.0 kcal/mol obtained with exact per-target offsets. The ranking of ligands within a target varies more widely (median Spearman $\rho$ of 0.32, from $-$0.41 to 0.89) and is rationalized by the structure-activity relationship of each series: Martini ranks ligands well when their affinity is driven by hydrophobicity, $\pi$-stacking, or size, and poorly when it is driven by hydrogen bonding or charge. Both trends follow from Martini's calibration against bulk partitioning, which captures neither the dielectric environment of a binding pocket nor the directionality of hydrogen bonds. While MMGBSA retains the atomistic detail needed to rank congeneric ligands, Martini yields physically meaningful free energies, and its coarse-graining maps many atomistically distinct molecules onto one representation, making it a complementary tool for rapidly spanning chemical space.
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Chemical Physics

Non-Perturbative Vibrational Excitation by Arbitrary Electric Fields from Classical Phase-Space Dynamics

Sameernandan Upadhyayula and Jiří J. L. Vaníček

We present a non-perturbative framework for the quantum treatment of vibrational excitation in molecular systems driven by electric fields with arbitrary time dependence. For harmonic potentials with linear dipole coupling, the field-induced dynamics is exactly described by a displaced coherent state, whose evolution is completely determined by a complex phase-space coordinate. Closed-form expressions for this coordinate reveal a clear distinction between resonant and non-resonant regimes. The resulting vibrational populations follow a Poisson distribution determined by a dimensionless time-dependent phase-space displacement, for both resonant and non-resonant driving. Resonant driving results in an enhanced phase-space displacement, whereas finite detuning between the driving and vibrational frequencies leads to an exponential suppression of the phase-space displacement and vibrational excitation. While the approach reduces to the standard time-dependent perturbation theory in the weak-field limit, it remains valid in the strong-field regime, where perturbative treatments fail. Our results provide a transparent phase-space picture of vibrational control and enable non-perturbative state preparation in ultrafast spectroscopy.
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Chemical Physics

Isotope Effects at Classical Cost through Mass-Differentiable Machine Learning

Ming-Zheng Du, Shi-Yu He, Jing Shen et al. (+5 more)

Isotope effects govern fractionation and modulate reactivity, with applications from hydrogen energy to environmental science and catalysis, yet predicting them requires resolving small isotope-dependent free-energy differences that remain very challenging for conventional path-integral simulations in complex systems. Here we introduce iso-EPIGS, a path-integral coarse-graining framework built on a mass-differentiable neural network that reconstructs the mass- and temperature-dependent path integral centroid free-energy surface. Classical molecular dynamics on the learned surface yields rigorous isotope-resolved thermodynamics without explicit path-integral sampling. Benchmarks spanning gas, liquid, and crystalline phases, including liquid water and oxalic acid crystal, reproduce reference path-integral isotope free-energy differences, enthalpies, and lattice parameters at near classical computational cost. Crucially, iso-EPIGS trained solely on all-H and all-D isotopologues retains high accuracy for unseen partially deuterated isotopologues, demonstrating robust transferability across nuclear masses. Iso-EPIGS makes accurate isotope-effect simulations feasible for complex systems and lays the groundwork for foundation models of isotope effects across chemical space.
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All authors Ming-Zheng Du, Shi-Yu He, Jing Shen, Ziyan Ye, Jia-Xi Zeng, Dong H. Zhang, Venkat Kapil, Wei Fang

Wednesday 7 October

Chemical Physics

Looking Under the Streetlight: Evaluation in Generative Molecular Dynamics

Simon Olsson, Frank Noé, Grant M. Rotskoff et al. (+1 more)

This position paper argues that the generative molecular dynamics (GenMD) community is not properly evaluating its progress: current evaluations let a model match what is reported while being arbitrarily wrong on what was claimed, which risks over-claiming advantage over classical baselines. This reflects a structural misalignment between common evaluation practices and the scientific tasks the field sets for itself. The reason is that the ground truth—exhaustive molecular dynamics on the systems of interest—is computationally costly, and this cost is what motivates the field. With ground truth inaccessible, evaluation drifts toward convenient proxies, and the resulting norms entrench easily. We identify misaligned evaluation patterns that persist as a community-level equilibrium, and propose concrete observables, reporting standards, and benchmark designs, both computational and experimental, that better reflect what GenMD aspires to deliver. Our aim is to give the field shared language and tools for evaluation that match its scientific ambitions before today's conventions calcify into norms.
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All authors Simon Olsson, Frank Noé, Grant M. Rotskoff, Kresten Lindorff-Larsen

Chemical Physics

Visualizing Three-Dimensional Quantum Fluctuations of Ground-State C$_3$H$_4$ via Deep Sub-Angstrom Coulomb Explosion Imaging

Mei Wang, Yue Gao, Hang Yuan et al. (+6 more)

Coulomb explosion imaging (CEI) is a powerful tool for determining static geometries of isolated gas-phase molecules. In this work, taking allene and propyne as prototype, we demonstrate sub-angstrom resolution achieved with highly charged ion-induced CEI. Using 41.9 keV/u Xe$^{20+}$ beam, minute variations of CC single, double and triple bond lengths are clearly visualized, indicating that an ultrahigh resolution of 0.1 $\mathring{\mathrm{A}}$ is achieved. This unprecedented resolution not only makes it possible to distinguish CC bonds with different bond orders, but also lays a solid foundation for direct observation of quantum fluctuations inherent to 3D structure of a ground-state molecule. Notably, the coupled collective motion of the two CH$_2$ moieties spaced by a central carbon within allene is unambiguously visualized in our measurements.
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All authors Mei Wang, Yue Gao, Hang Yuan, Yang Wang, Bo Yang, Shaofei Gu, Shaofeng Zhang, Xinwen Ma, Shenyue Xu

Chemical Physics

Ab Initio Investigation of Excited States and Absorption Spectra of Small Mercury Clusters (Hg$_{2-5}$)

Michal Novotný and František Karlický

We report a systematic ab initio investigation of the excited states and absorption spectra of small mercury clusters (Hg$_{\mathrm{2-5}}$). Benchmarking multi-reference configuration interaction (MR-CISD) and equation-of-motion coupled-cluster (EOM-CCSD) methods shows that EOM-CCSD/aug-cc-PVTZ-PP reproduces atomic excitation energies within $\pm$500 cm$^{-1}$ of experiment, whereas MR-CISD deviates by about $\pm$1100 cm$^{-1}$. For the mercury dimer, EOM-CCSD potential energy curves yield absorption bands in excellent agreement with experimental transitions, while asymptotic excitation energies closely match atomic references. Extending this methodology, we present the first systematic ab initio study of absorption spectra of Hg$_{\mathrm{3}}$, Hg$_{\mathrm{4}}$, Hg$_{\mathrm{5}}$, which display broad bands in the ranges of 37000-60000 cm$^{-1}$. The consistent agreement with experimental benchmarks and diagnostics confirming single-reference character validates EOM-CCSD as a robust approach for describing excited states and optical spectra of mercury clusters.
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Chemical Physics

Overcoming the limitations of body-ordered potentials for atomistic machine learning

Filippo Bigi, Michelangelo Domina, Maximilian Lloyd Ach et al. (+5 more)

Machine-learning interatomic potentials have become indispensable tools in atomistic simulations. The most popular models rely heavily on physical priors, such as locality, smoothness and symmetry, that are assumed to improve the accuracy and transferability of the trained models. However, recent evidence suggests that, in the data-rich regime, unconstrained models that learn symmetry from the data can achieve very competitive accuracy and computational efficiency, without sacrificing stability and generalization power. Many equivariant symmetric architectures historically rely on the assumption that the interatomic potential can be approximated well by a convergentcluster expansion, i.e., a decomposition in terms associated to atomic pairs, triplets, quadruplets, and higher-order tuples. We describe an architecture that incorporates locality, smoothness, and symmetry priors, but that – thanks to a computationally efficient tensor product formulation – does not assume low-order truncation of the body-ordered series.
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All authors Filippo Bigi, Michelangelo Domina, Maximilian Lloyd Ach, Sergey N. Pozdnyakov, Paolo Pegolo, Joseph W. Abbott, Kevin K. Huguenin-Dumittan, Michele Ceriotti

Chemical Physics · Cross-listed from quant-ph

Coherence-assisted quantum state preparation and thermal control through repeated interactions

Alessandro Prositto and Dvira Segal

We investigate the relaxation dynamics and steady state of a qubit interacting with a coherent environment through an energy-conserving flip-flop interaction within the Markovian repeated-interaction framework. We derive an exact analytical solution for the evolving and stationary state, nonperturbative in the environmental coherence. We show that environmental coherence provides a resource for dissipative state preparation by expanding the set of accessible steady states. In particular, coherent ancillas can increase the system ground- state population beyond that of the bath, corresponding to an effective temperature below the bath temperature, and enhance its steady-state purity, with these effects controlled by the interplay between the system energy scale and the system-ancilla coupling. Nevertheless, we prove that the purity of the system can never exceed the purity of the ancilla. We further analyze the thermodynamics of the protocol and show that environmental coherence can modify and even reverse the natural direction of heat transfer, giving rise to anomalous heat flow. Remarkably, for fixed interaction parameters, the direction of the coherence-induced heat transfer is governed by the relative phase between the system and ancilla coherence, whereas their magnitudes determine the amount of heat exchanged. Our results establish environmental coherence as a resource for controlling steady-state preparation and energy transfer in repeated-interaction dynamics.
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Chemical Physics · Cross-listed from cs.LG

NEMORA: Neural Equivariant Multipole Operators for Long-Range Atomistic Learning

Jay L. Kaplan, Samuel Varner, Rebecca Willett et al. (+1 more)

Equivariant graph neural networks have emerged as foundational architectures for machine-learned interatomic potentials, approaching quantum-chemical accuracy at a fraction of the computational cost. These models describe local atomic environments accurately, but finite spatial cutoffs truncate long-range information flow, and stacking message-passing layers can lead to over-smoothing and over-squashing. Existing long-range extensions either prescribe a fixed analytical propagation kernel, restrict long-range communication to scalars or degree-preserving channels, are only approximately equivariant, or incur super-linear computational cost. Combining learnable long-range equivariant transport with multiscale many-body expressivity and efficient scaling for larger systems remains a central challenge. We introduce Neural Equivariant Multipole Operators (NEMORA), a neural equivariant extension of the Fast Multipole Method (FMM) for learning long-range tensorial representations. NEMORA generalizes the FMM's analytical multipole expansion and translation operators to learned equivariant counterparts on an adaptive spatial hierarchy. Its operators couple angular degrees and form many-body interactions across length scales, retaining the FMM's hierarchical organization and analytical radial factors as physical inductive biases while learning data-dependent long-range couplings. NEMORA evaluates in linear time and memory complexity, allowing it to treat larger systems than other long-range methods reaching hundreds of thousands of atoms, and it augments both symmetry-constrained and unconstrained short-range backbones. On non-local benchmarks, it reduces force and energy errors relative to the short-range backbones by over an order of magnitude and up to three orders of magnitude, respectively, which is better than or competitive with existing long-range extensions in accuracy.
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All authors Jay L. Kaplan, Samuel Varner, Rebecca Willett, Juan J. de Pablo

Chemical Physics

General Time-Dependent Surface Flux for Multiple Ionization and Fragmentation of Molecules. I: General Theory

Stefanos Carlström and Serguei Patchkovskii

We introduce a method for efficiently computing multiple photofragmentation of atoms and molecules into photoelectrons and nuclear fragments. The method is a generalization of the time-dependent surface flux originally introduced for single and double photoionization.

Chemical Physics

LLM-Assisted Generation of Transparent, Open-Source Multiphysics Models of Electrochemical Devices

Sebastian Castro, Maya F. Schuchert, Spencer A. McCluskey et al. (+2 more)

Multiphysics continuum models are powerful tools for studying electrochemical devices, enabling in silico reactor design and resolution of local pH, potential, and concentration fields that govern device performance but are difficult to measure experimentally. However, constructing such models requires substantial numerical expertise or reliance on proprietary software. Here, we show that frontier large language model agents can remove this implementation burden while keeping the underlying physics under researcher control. Using one-dimensional electrochemical CO2 reduction to CO in a porous gas diffusion electrode as a test case, we develop a machine-readable, human-specified modeling harness containing governing equations, parameters, numerical methods, logical build stages, and human-verifiable checkpoints. From this specification, the agent reproducibly constructs complete multiphysics models in open-source Julia. Independently built models, including fully autonomous agent-built models, agree with an equivalent COMSOL implementation to within 0.7% of the peak CO partial current density, and with one another to within 0.04%. Systematically planted errors demonstrate the importance of explicit specifications for reproducibility and reveal the agent's capabilities and limitations in debugging model physics. This framework establishes a more transparent approach to multiphysics modeling in which physical descriptions and governing equations, rather than specialized code, become the primary inputs for computational model development.
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All authors Sebastian Castro, Maya F. Schuchert, Spencer A. McCluskey, Eric W. Lees, Justin C. Bui

Chemical Physics · Cross-listed from cs.LG

Physics-Aligned Electronic Ground-State Learning Improves Generalization

Eike S. Eberhard, Xaver Kainz, Viktor Kotsev et al. (+2 more)

Machine-learned interatomic potentials (MLIPs) excel at in-distribution tasks, accelerating drug and material development, yet they struggle to generalize out-of-distribution. We propose to push the cost-accuracy Pareto frontier by designing observable-agnostic electronic ground-state descriptor models (GSMs) with computational costs situated between MLIPs and Kohn-Sham density functional theory (KS-DFT). We align the learning objectives and architectures of GSMs with the governing equations of KS-DFT by enforcing physical constraints and removing optimization pressure on unphysical or irrelevant degrees of freedom. In our size-extrapolation experiments from QM9 to QM40, our combined contributions OrthoNormal-Loss (ON-Loss) and Grassmann Restricted Occupied-Orbital Training (GROOT) reach a 79.1% energy and 83.4% force mean absolute error (MAE) reduction over previous state-of-the-art density GSMs. For Hamiltonian GSMs, ON-Loss and Residual Optimal-gauge Conditioning-aware KS-Eq. Training (ROCKET) together reduce the energy and force MAEs of the strongest baseline by 99.8% and 95.9%, respectively. Using a self-consistency rejection criterion, we filter out extrapolation errors on QMugs, rejecting fewer than 0.4% of predictions while reaching an energy MAE of 0.07 mHa. Finally, we demonstrate the efficiency of label-free self-consistency fine-tuning, and transfer GSMs to reactive chemistry in Transition1x, reaching energy errors below chemical accuracy.
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All authors Eike S. Eberhard, Xaver Kainz, Viktor Kotsev, Abdulrahman Aldossary, Stephan Günnemann

Chemical Physics · Cross-listed from physics.ins-det

Wavelength-Resolved Timing of Near-Infrared Scintillation in Gaseous Xenon

Robert Hammann, Steffen Form, Humaira Nazneen et al. (+3 more)

The near-infrared (NIR) scintillation signal of xenon has the potential to enhance the performance of xenon-based detectors, but a robust understanding of its properties is a prerequisite for its application. In this work, we measure the NIR time response for $\alpha$-particle interactions in gaseous xenon in 12 wavelength bands spanning approximately $(950-1620)\,$nm. The time response is decomposed into a fast (ns-scale) component and a dominant slow ($\mu$s-scale) component. The fast-component spectrum coincides with strong atomic emission lines, predominantly 6p$\,\to\,$6s, whereas the slow-component spectrum follows the broad continuum centred around $1.3\,\mu$m. The pressure dependence of the continuum can be described by a two-step kinetic model in which the emitting state is formed by a three-body process and depopulated by a two-body collisional process, with density-independent terms in both rates. Interpreting the slower of these as radiative decay yields an intrinsic lifetime of $\sim3\,\mu$s. Theoretical calculations identify a neutral-excimer transition $0_u^- \rightarrow 0_g^-$ and an ionic-dimer transition $1/2_{u} \rightarrow 1/2_g$ as plausible candidates for the continuum emission, with the ionic-dimer transition showing better overall agreement with the measurements.
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All authors Robert Hammann, Steffen Form, Humaira Nazneen, Gabriel Schöpfer, Milan Ončák, Teresa Marrodán Undagoitia

Chemical Physics

Cotunneling-Assisted Redistribution of Nonpassivity in a Photosynthetic Junction

Manjet Rajak, Trishna Kalita, Debasish Sharma et al. (+1 more)

We investigate how cotunneling affects passive-state ordering in a Photosystem II reaction center modelled as a nonequilibrium molecular junction. We use a full pigment excitation manifold, with excitonic and charge-transfer rates computed within a Nakajima-Zwanzig formalism using realistic spectral densities. Cotunneling is introduced through a microscopically constructed doubly reduced acceptor state obtained from relevant quinone-side two-electron configurations, while photoexcitation is allowed into the full excitonic manifold. Passive-state permutations are quantified through ergotropy and energetic capacitance. We find that thermodynamic smoothness in ergotropy and energetic capacitance can conceal microscopic state rearrangements. Cotunneling redistributes the extractable nonequilibrium energy among the quinone acceptor, the donor-pheophytin radical pair, and excitonic states with strong contributions from pigments on the inactive branch. At high Coulomb interaction, cotunneling produces no passive-state reordering. Piecewise-linear relations among ergotropy, energetic capacitance, and mean energy further reveal the population reorderings generated by cotunneling.
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All authors Manjet Rajak, Trishna Kalita, Debasish Sharma, Himangshu Prabal Goswami

Chemical Physics

Nonuniform Screening Reshapes Collective Excitons in Molecular Aggregates from Stochastic Bethe-Salpeter Theory

Barry Y. Li, Chern Chuang, Tim Duong et al. (+3 more)

We build and apply an $\textit{ab initio}$ stochastic Bethe-Salpeter Equation (sBSE) approach to planar cyanine dye aggregate clusters containing up to 2,856 valence electrons. Using a transferable, parameterized screened exchange kernel, we resolve dielectric response, exciton delocalization, and optical spectra within a unified many-body framework. Remarkably, the sBSE transition densities validate the Frenkel exciton picture in real space and provide a practical first-principles route to its screened couplings. The calculations reproduce $\textit{H}$-, $\textit{I}$-, and $\textit{J}$-like spectral evolution and reveal that spatially dependent screening does not merely shift excitonic bands, but reshapes their dispersion, leading to changes in the relative energies of bright and dark exciton states. These results establish sBSE as a predictive framework for large molecular aggregates.
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All authors Barry Y. Li, Chern Chuang, Tim Duong, Tucker Allen, Justin R. Caram, Daniel Neuhauser

Chemical Physics · Cross-listed from cond-mat.mtrl-sci

Electronic Properties of Ladder-Type Phenylenes Studied by Thermally-Assisted-Occupation Density Functional Theory

Tsu-Hsuan Wang and Jeng-Da Chai

Accurate prediction of the electronic properties of extended $\pi$-conjugated systems with radical character remains a major theoretical challenge. To overcome this challenge, thermally-assisted-occupation density functional theory (TAO-DFT) has been developed in recent years. In this study, we employ TAO-DFT to systematically explore the electronic properties of ladder-type phenylenes ($n$-LPs), containing $n$ linearly fused four-membered carbon rings. Our calculations reveal that all investigated $n$-LPs (with $n$ = 1 ~ 40) possess singlet ground states. With increasing $n$-LP length, we observe a transition from the nonradical character of shorter $n$-LPs to the polyradical character of longer $n$-LPs. Notably, we identify a distinct damped periodic oscillation in the radical character of $n$-LPs, featuring highly correlated hotspots at specific lengths ($n = 3k - 1$, where $k$ are positive integers). The real-space representation of active orbitals confirms this global electronic behavior is governed by the intrinsic structural periodicity and completely delocalized nature of the active orbitals along the central ladder framework. These findings provide fundamental insights into the size-dependent electronic properties of $n$-LPs, guiding their rational design for future nanomaterial applications.
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Chemical Physics

Interfacial Water Responds Linearly to Charge yet Is Charge-Asymmetric

Yair Litman, Yongkang Wang, Stephen Cox et al. (+1 more)

The organization of interfacial water shapes the electric double layer behavior in aqueous electrolytes. Asymmetries upon charge reversal are commonly attributed to specific ion adsorption or surface chemistry. Yet it is unresolved whether interfacial water is net oriented at zero charge, and whether such orientation alone makes its response charge-asymmetric. Here, using electrochemical heterodyne-detected sum-frequency generation spectroscopy and constant-potential molecular dynamics simulations, we resolve the absolute orientation of water at a weakly interacting graphene electrode. We show that interfacial water retains a net H-down orientation, with hydrogens pointing toward the bulk, at zero net surface charge. Superimposed on this offset, the field-induced reorientation is linear and symmetric upon charge reversal, independent of how the charge is introduced or distributed. The zero-charge offset therefore shifts the potential of zero water orientation negatively relative to the potential of zero charge, making the interfacial water response intrinsically charge-asymmetric. These results establish an electrostatic baseline against which extrinsic contributions at electrified interfaces can be isolated.
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All authors Yair Litman, Yongkang Wang, Stephen Cox, Mischa Bonn

Chemical Physics · Cross-listed from quant-ph

Spurious zero-dispersion continua in full $(2,q)$-positivity: A linear hierarchy-depth lower bound from an exactly solvable counting operator

Maho Nakata

Variational two-particle reduced-density-matrix methods impose hierarchies of semidefinite constraints. We ask whether a fixed level of such a hierarchy can recover even an elementary many-fermion spectrum, using the dispersion test, in which a value is accepted as an eigenvalue when the minimized dispersion vanishes. For an exactly solvable operator that counts fermions in one half of the spin orbitals, whose spectrum consists of integers, we determine the complete set of accepted values at every level of the full hierarchy of particle-hole semidefinite constraints. Besides the integers, this set contains an entire interval of noninteger values unless the hierarchy level grows linearly with the particle number, and we give the exact threshold. The proof constructs explicit pseudo reduced density matrices that are diagonal in the occupation basis, obtained by continuing the occupation probabilities of a fixed-particle-number state to a noninteger particle number. Classical semidefinite constraints on occupation correlations, supplemented by nonnegative occupation-pattern probabilities, suffice to establish fermionic positivity. For this counting model the two relaxations have the same dispersion zero set, not necessarily the same feasible states, and a converse argument shows that no other false eigenvalues occur. The limitation is specific to the hierarchy: two-body inequalities that encode the integer spectrum would remove every false value but are not generated at a fixed level. We also verify that the full semidefinite constraints and their complete projection onto two-particle reduced-density-matrix space are equivalent in finite dimensions, so that the result applies equally to the polar formulation.
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Chemical Physics

How Good Is DFT for Solid-Liquid Interfaces? A Comparison With the Random-Phase Approximation for Water on Graphene

Xavier R. Advincula, Yair Litman, Jiuyang Shi et al. (+3 more)

Simulations of water at solid interfaces routinely disagree on basic properties, from contact angle to friction, depending on the model used, whether an empirical force field or a density functional theory (DFT) exchange-correlation (XC) approximation. Yet no accurate computational reference has been available to determine which, if any, is reliable. Here we assess XC approximations spanning the rungs of Jacob's Ladder against the random-phase approximation (RPA) at the graphene-water interface. Using machine-learned potentials (MLPs) trained on both DFT and RPA data, we achieve the extensive sampling required to characterize interfacial structure, wettability, friction, and vibrational sum-frequency generation spectra. We find that XC approximations disagree substantially with RPA and with each other. To make sense of this, we introduce a transferable, multi-observable scoring framework that distills each functional's agreement with RPA into a single measure. Six functionals emerge as reliable starting points for studies of graphene-water and other dispersion-dominated interfaces, namely B3LYP-D3(0), revPBE-D3(0), revPBE-D3(BJ), B97M-rV, r$^{2}$SCAN, and revPBE0-D3(0). Notably, this ranking follows no simple rule based on functional family or rung of Jacob's Ladder. What does hold across functionals is that dynamical and spectroscopic properties tend to be harder for DFT to reproduce than structural ones, with direct consequences for functional selection. Our framework also offers a general strategy for benchmarking any atomistic model, including the new generation of foundational MLPs, against high-accuracy references at solid–liquid interfaces. Beyond simulation, this work identifies which models can be trusted to connect measured contact angles, friction, and vibrational spectra to the molecular structure behind them.
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All authors Xavier R. Advincula, Yair Litman, Jiuyang Shi, Flaviano Della Pia, Christoph Schran, Angelos Michaelides